Hi scartch,
Although TiTou's suggestion of using the derivative will definitely work to find all the peaks, I do not believe it will work with your particular application. The purpose of the Threshold Peak Detector is to eliminate any false peaks that may be introduced by noise. For instance, the data you provided would count peaks for the transitions between .003 and .005 and between .005 and .007. These peaks will be counted due to noise in your signal, but the Threshold Peak Detector will filter it out with the use of the threshold and width inputs.
This question is very similar to
this thread. I suggest using the original thread since it is on the appropriate board. As Jennifer alluded to in the original thread, I suggest taking subsets of your data, finding the average, and normalizing the data (by dividing the average). Then you can use the same threshold and width for all of your data. Appropriate values for threshold and width will depend on the data. It is a very common method to use a moving average filter (described above) to correct the baseline wandering problem. I hope this helps!